Buch, Englisch, 336 Seiten
Buch, Englisch, 336 Seiten
ISBN: 978-1-394-38028-2
Verlag: John Wiley & Sons Inc
Harness artificial intelligence to develop stress-resilient crops for sustainable agriculture
Machine Learning and AI for Precision Plant Epigenetics demonstrates how to develop climate-resilient crops by integrating AI with RNA-based epigenetic technologies. Edited by Professor Jen-Tsung Chen, a leader in plant biotechnology, this volume integrates insightful contributions from experts around the world that discuss how ML and AI models can revolutionize plant breeding and crop improvement to ensure food security under changing environmental conditions.
The book explores applications across sixteen chapters, covering AI-driven epigenome engineering, CRISPR/Cas9-mediated precision editing, intelligent approaches to combat abiotic and biotic stresses, and AI-enabled RNA interference. It explores the use of AI models for studying non-coding RNAs, predicting plant epigenetic landscapes, unlocking heat stress memory mechanisms, and uncovering plant-microbiome interactions critical for productivity.
The book: - Integrates machine learning with RNA technologies to enhance epigenetic modifications through non-coding RNAs and refine gene silencing capabilities
- Demonstrates AI-advanced CRISPR/Cas systems for precision genome engineering to develop crops with enhanced quality, yield, and stress resilience
- Provides strategies for studying plant epigenetic landscapes under abiotic stress and developing intelligent priming systems against biotic threats
- Features contributions from leading international researchers at prestigious institutions
- Addresses ethical and regulatory considerations essential for responsible implementation of artificial intelligence in agricultural biotechnology and crop development
This essential resource is tailored for researchers in plant biology, stress physiology, crop breeding, computational biology, and bioinformatics. It offers a forward-looking perspective on developing sustainable agriculture systems that support global food security in an era of climate change and increasing environmental challenges.
Autoren/Hrsg.
Fachgebiete
Weitere Infos & Material
List of Contributors
About the Editor
Preface
Chapter 1 Machine Learning for Precision Epigenetic Modification in Plants
Chapter 2 AI-Driven Precision Plant Epigenetic Regulation under Changing Climate
Chapter 3 AI-Driven Plant Epigenome Engineering for Developing Resilient Crops
Chapter 4 AI-Based Studies on Epigenetic Mechanisms: Highlighting Plant Adaptation and Domestication
Chapter 5 AI Models for Studying Plant Epigenetics and Epigenomics
Chapter 6 AI-Based Approaches for Studying Plant Epigenetic Landscapes under Abiotic Stress
Chapter 7 AI-Based Whole Genome Prediction for Diverse Plant Epigenetic Modulations
Chapter 8 Intelligent Priming System for Combating Biotic Stress
Chapter 9 AI Technology for Studying Plant Non-Coding RNAs
Chapter 10 AI-enabled Plant RNA Interference
Chapter 11 AI Models for Uncovering Plant-Microbiome Interactions
Chapter 12 AI-Assisted Omics Tools for Predicting Functions of Plant RNAs
Chapter 13 The Integration of Artificial Intelligence and Big Data in Plant Epigenetics
Chapter 14 AI-Omics-Epigenetics Integration in Plants: Highlighting the Study of MicroRNAs
Chapter 15 Machine Learning and Computational Biology-Based Epigenetics for Uncovering Plant Adaptive Evolution
Chapter 16 Ethical and Regulatory Considerations of Artificial Intelligence in Agriculture
Index
